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Forecasting the effect of PTP policy on changes of travel patterns with ordered logit model

机译:用有序logit模型预测PTP政策对出行方式变化的影响

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Public Transport Priority (PTP) is adopted as basic transport policy in many metropolitan cities, especially like Beijing, with great number of population and rapid urban economic development. This study mainly discusses how PTP measures affect travelers' behavior, what type and levels of PTP measures increase the acceptance of public travel modes, and how PTP measures take a positive effect in Beijing city. Through the analysis by an ordered logit model, it is revealed that respondents with lower incomes are more likely to use public travel modes instead of paying comparatively high car-costs. Moreover, it is also found that respondents able to obtain transport subsidies are less likely to take bus, subway and so on. About the transport service attributes of the proposed logit model, it is clarified that travel time is the most important consideration for travelers and, in contrast, prices of tickets are usually ignored. Based on the study of the newly developed ordered logit model and the development plan of public transport service in near future published by Beijing Municipal Committee of Communication, it can be first concluded that if the average in-vehicle time of public travel models decreases from 42.6 minutes to 32 minutes, about 385.8 thousand trips by private car everyday will shift to public transport sector. At the same time, given about 3.6 minutes' decrease of average public travel time for waiting and transfer, around 164.2 thousand trips by private car will be eliminated.
机译:在许多人口众多且城市经济飞速发展的大城市,尤其是北京等大城市中,公共交通优先(PTP)被用作基本交通政策。本研究主要讨论PTP措施如何影响旅行者的行为,PTP措施的类型和水平如何提高人们对公共出行方式的接受程度,以及PTP措施如何对北京市产生积极影响。通过有序logit模型进行的分析表明,收入较低的被调查者更有可能使用公共出行方式,而不是支付相对较高的汽车费用。此外,还发现能够获得交通补贴的被调查者不太可能乘坐公交车,地铁等。关于所提出的logit模型的运输服务属性,需要说明的是,旅行时间是旅行者最重要的考虑因素,相反,票务价格通常被忽略。根据北京市交通委员会发布的最新开发的有序logit模型和近期公共交通服务发展计划的研究,可以首先得出结论,如果公共旅行模型的平均车内时间从42.6减少分钟到32分钟之间,每天大约有38.58万人次的私家车旅行将转移到公共交通部门。同时,由于等待和转移的平均公共旅行时间减少了约3.6分钟,因此将消除约16.42万人次的私家车出行。

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